Stockage et transmission des données 1: introduction; besoin de structure

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Page 3 of 4

Covers advanced data wrangling techniques using Hadoop, focusing on Hive and HBase integration.

Covers the fundamentals of big data ecosystems, focusing on technologies, challenges, and practical exercises with Hadoop's HDFS.

Explores challenges of handling massive data in the era of big data, discussing solutions like MapReduce and Spark.

Discusses file systems, focusing on data organization, indexing techniques, and their impact on database performance.

Covers the origins, properties, and types of NoSQL databases, focusing on MongoDB and the CAP theorem.

Explores indexing in database systems, covering storage, files, and efficient data retrieval techniques using various types of indexes.

Covers the storage of geographic information using vector and grid formats, coordinate reference systems, and image formats.

Covers the Spark runtime architecture, including RDDs, transformations, actions, and caching for performance optimization.

Covers the basics of storage technologies and database system architecture.

Covers the essentials of data science, including data handling, visualization, and analysis, emphasizing practical skills and active engagement.